Difference between revisions of "MANUELA"
| Line 4: | Line 4: | ||
Six mayor topic have been addressed: | Six mayor topic have been addressed: | ||
* large scale patterns in meiobenthic diversity and community composition | * large scale patterns in meiobenthic diversity and community composition | ||
| − | * the universal response of | + | * the universal response of meiobenthos to disturbance, |
* patterns in marine nematode morphometry, | * patterns in marine nematode morphometry, | ||
* patterns in deep-sea nematode communities, | * patterns in deep-sea nematode communities, | ||
* prediction of nematode biodiversity by using artificial neural networks | * prediction of nematode biodiversity by using artificial neural networks | ||
| − | * large scale patterns in | + | * large scale patterns in harpacticoid copepod community composition and diversity. |
Revision as of 12:39, 21 August 2009
Traditionally, marine researchers collect data in their own field of expertise, often with a confined temporal and spatial range. These data are then normally used in a rather limited context. The Marine Biodiversity and Ecosystem Functioning Network of Excellence (MarBEF) implemented besides 17 other research projects the MANUELA project. MANUELA – Meiobenthic and Nematode biodiversity: Unravelling Ecological and Latitudinal Aspects – aimed to integrate the scattered information on the dynamics and the functional role of meiofauna into one single database so that joint analyses could be performed. The MANUELA project gave scientist the opportunity to perform large-scale analyses of the nematode and copepod communities on an European and even larger scale. Six mayor topic have been addressed:
- large scale patterns in meiobenthic diversity and community composition
- the universal response of meiobenthos to disturbance,
- patterns in marine nematode morphometry,
- patterns in deep-sea nematode communities,
- prediction of nematode biodiversity by using artificial neural networks
- large scale patterns in harpacticoid copepod community composition and diversity.
